Langhui
Agent Assessment and Task Environment

Agent Assessment and Task Environment HOT

Occupational workflow — End environment — Tool use — End-to-end process automation

For the 2026 Smart (Agent) Competency Assessment and Training Needs, provide 11 types of real, reversible mission environment data: from occupational long-distance work streams such as investment/advisory/legal to terminal barriers, 10 full-power tools and business processes. All tasks are supported by environmental mirrors, state assertions and validation scripts.

Dataset Catalog

Section Positioning and Development Value

Real job caliber

The task is derived from a real career delivery scene, and the rating criteria are set by professional experts to avoid “failure to work in examinations”.

Recoverable environment

Mission environment Docker is re-established and state can be asserted in scripts, and the results can be compared across teams and horizontally.

High Distinction

Priority is given to building the current directions of SOTA's underperformance (TB 3.0% only 15-26%, Automation Bench 18-30%), opening the model gap.

Training and evaluation

The same task can be used both for post-training (the standard gold-bearing track) and for evaluation purposes directly.

Data and Task Composition, Scale Description

Task Scale

Single category: 1,500–12 000 mission environments; support delivery by occupation, tool type, difficulty classification.

Environmental form

Docker mirror / Simulate Office Environment / Real Terminal Sandbox three types of scripts that are accompanied by initialization and reset.

Annotation Granularity

Task level target + step level action sequence + status assertion point + rating rubric level four label.

Difficulty classification

The status of the status of the current list of unsaturated slots is divided into the three tranches of Standard / Hard / Frontier, which is the current file alignment.

Typical Use Cases

Smart body competency assessment

Provide model manufacturers and assessment agencies with reversible, anti-pollution high-level rating sets.

After-training for Agent

The RL rewards the signal by using gold standard tracks and assertions feedback to train real capacity to work.

Enterprise Automation Selection

Horizontal comparison of Agent products with real business process tasks to underpin procurement decisions.

Security and border studies

Research and assessment of safety-related capabilities such as RSI, rewarding, ultra vires operations.

Delivery Format and Specifications

Delivery Format

Task package (Docker mirror + initial state) + Verify script + standard gold track JSONL + rubric score sheet.

Core Fields

task_id、env_image、goal、toolset、assertions、gold_trajectory、rubric、difficulty、metrics。

Quality Control Standards

Environmental operationality 100%, assured script certainty verification, standard gold track manual review pass rate 98%.

Delivery Cycle

Standard 4-6 weeks; occupational and end-of-life environmental 6-8 weeks; support for rolling amplification.

Licensing and Compliance

Commercial use authorization, full de-identification of operational data, and data processing and compliance documentation.

Example Description

Check script for Terminal-Bench type 3.0 (select)
#!/usr/bin/env rash
You know, set-e.
# Claim 1: Service started and monitored 8080
It's all right, it's all right.
# Claim 2: Profile strengthened
"Permit RootLogin no" /etc/ssh/shd config exit 1
# Claim 3: Return test passed
cd /app & /amp; /amp; pytest-q testes/ tail-1 root-q "passed" exit1
"PASS."
Toolathlon Tool Call-Fix Criteria (Excerpt)
Other Organiser
"Task id": "Toolathlon-0213",
"goal": "Check last week's orders and generate reconciliation forms for finance."
"gold security":
"Tool": "db.query", "args": "range": "last week" ,
"Tool": "sheet."
"Tool": "mail.send", "args": "to": "finance@corp.com", "attach": "$2.file"
I don't know.
"fallback with csv export"
"Metrics":
♪ I'm sorry ♪

Agent assessment environment needs customisation?

Changsha Langhui Information Technology Co., Ltd. The DataAssetsAPI platform supports flexible combinations of occupations, tool ecology, difficulty bands and environmental patterns, providing a prototype environmental preview with private evaluation.

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